High frequency soil polarization can phenotype crop roots noninvasively

Abstract

Noninvasive and nondestructive root phenotyping techniques under field conditions are sorely needed to advance plant root science. Soil polarization measured by electrical capacitance (EC soil ) has the potential to meet this requirement, but whether it specifically detects root properties remains unexplored. We carried out manipulative experiments where wheat ( Triticum aestivum L.) and maize ( Zea mays L.) roots were buried in soil or immersed in hydroponic solution combined with pot trials to reveal the mechanism of root trait detection by EC soil , while a field experiment was conducted to test its feasibility to determine root depth distribution. We found that EC soil measured at low current frequency (< 1 kHz) was not significantly affected by the addition of roots to the system either by burying roots in soil or immersing them in solution. At frequency greater than10 kHz a shift occurred, and root polarization contributed more to EC soil which was positively correlated with root volume. When EC soil was measured at high frequency (30 kHz −100 kHz) it was well correlated with root volume vertical distribution in the field. The measurement error after soil moisture calibration at depths of 10 cm, 20 cm, 30 cm and 40 cm was 0.4%, 12.0%, 1% and 34%, respectively. Our results demonstrate that EC soil is a robust method to measure in situ root distribution and we believe the newly available high frequency measurement equipment combined with novel root prediction models will enable EC soil to be widely used for root phenotyping in the future.

Plant phenotyping relevance

高周波土壌電気容量を用いて、根体積と根の垂直分布を非侵襲的に測定する植物フェノタイピング手法を開発・検証しており、方法自体が研究の中心である。

Code and data availability

The paper states its study data are publicly available on ScienceDB, but no specific dataset identifier or direct dataset URL is given—only the generic ScienceDB site—so the paper-specific EC/root phenotype data cannot be directly located without contacting the authors. No author analysis code or trained models are avo

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